ArticleScientific reports2017
A time-varying biased random walk approach to human growth.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed, 13 citations in OpenAlex.
- Mixed evidence for stress effects on cortisol-testosterone coupling in Syrian refugee and Jordanian non-refugee adolescents.Psychoneuroendocrinology · 2026Article
- A causal model of human growth and its estimation using temporally sparse data.Royal Society open science · 2025Article
- Short-term dynamics of linear growth among Peruvian infants in the first year of life in a population with linear growth faltering.American journal of human biology : the official journal of the Human Biology Council · 2024Article
- An enhanced topologically significant directed random walk in cancer classification using gene expression datasets.Saudi journal of biological sciences · 2017Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
Growth and development are dominated by gene-environment interactions. Many approaches have been proposed to model growth, but most are either descriptive or describe population level phenomena. We present a random walk-based growth model capable of predicting individual height, in which the growth increments are taken from time varying distributions mimicking the bursting behaviour of observed saltatory growth. We derive analytic equations and also develop a computational model of such growth that takes into account gene-environment interactions. Using an independent prospective birth cohort study of 190 infants, we predict height at 6 years of age. In a subset of 27 subjects, we adaptively train the model to account for growth between birth and 1 year of age using a Bayesian approach. The 5-year predicted heights compare well with actual data (measured height = 0.838*predicted height + 18.3; R
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.